Metadata-Version: 2.4
Name: lllm-core
Version: 0.1.0
Summary: Low-Level Language Model framework for building LLM agentic systems.
Author: Junyan Cheng
License:                                  Apache License
                                   Version 2.0, January 2004
                                http://www.apache.org/licenses/
        
           TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
        
           1. Definitions.
        
              "License" shall mean the terms and conditions for use, reproduction,
              and distribution as defined by Sections 1 through 9 of this document.
        
              "Licensor" shall mean the copyright owner or entity authorized by
              the copyright owner that is granting the License.
        
              "Legal Entity" shall mean the union of the acting entity and all
              other entities that control, are controlled by, or are under common
              control with that entity. For the purposes of this definition,
              "control" means (i) the power, direct or indirect, to cause the
              direction or management of such entity, whether by contract or
              otherwise, or (ii) ownership of fifty percent (50%) or more of the
              outstanding shares, or (iii) beneficial ownership of such entity.
        
              "You" (or "Your") shall mean an individual or Legal Entity
              exercising permissions granted by this License.
        
              "Source" form shall mean the preferred form for making modifications,
              including but not limited to software source code, documentation
              source, and configuration files.
        
              "Object" form shall mean any form resulting from mechanical
              transformation or translation of a Source form, including but
              not limited to compiled object code, generated documentation,
              and conversions to other media types.
        
              "Work" shall mean the work of authorship, whether in Source or
              Object form, made available under the License, as indicated by a
              copyright notice that is included in or attached to the work
              (an example is provided in the Appendix below).
        
              "Derivative Works" shall mean any work, whether in Source or Object
              form, that is based on (or derived from) the Work and for which the
              editorial revisions, annotations, elaborations, or other modifications
              represent, as a whole, an original work of authorship. For the purposes
              of this License, Derivative Works shall not include works that remain
              separable from, or merely link (or bind by name) to the interfaces of,
              the Work and Derivative Works thereof.
        
              "Contribution" shall mean any work of authorship, including
              the original version of the Work and any modifications or additions
              to that Work or Derivative Works thereof, that is intentionally
              submitted to Licensor for inclusion in the Work by the copyright owner
              or by an individual or Legal Entity authorized to submit on behalf of
              the copyright owner. For the purposes of this definition, "submitted"
              means any form of electronic, verbal, or written communication sent
              to the Licensor or its representatives, including but not limited to
              communication on electronic mailing lists, source code control systems,
              and issue tracking systems that are managed by, or on behalf of, the
              Licensor for the purpose of discussing and improving the Work, but
              excluding communication that is conspicuously marked or otherwise
              designated in writing by the copyright owner as "Not a Contribution."
        
              "Contributor" shall mean Licensor and any individual or Legal Entity
              on behalf of whom a Contribution has been received by Licensor and
              subsequently incorporated within the Work.
        
           2. Grant of Copyright License. Subject to the terms and conditions of
              this License, each Contributor hereby grants to You a perpetual,
              worldwide, non-exclusive, no-charge, royalty-free, irrevocable
              copyright license to reproduce, prepare Derivative Works of,
              publicly display, publicly perform, sublicense, and distribute the
              Work and such Derivative Works in Source or Object form.
        
           3. Grant of Patent License. Subject to the terms and conditions of
              this License, each Contributor hereby grants to You a perpetual,
              worldwide, non-exclusive, no-charge, royalty-free, irrevocable
              (except as stated in this section) patent license to make, have made,
              use, offer to sell, sell, import, and otherwise transfer the Work,
              where such license applies only to those patent claims licensable
              by such Contributor that are necessarily infringed by their
              Contribution(s) alone or by combination of their Contribution(s)
              with the Work to which such Contribution(s) was submitted. If You
              institute patent litigation against any entity (including a
              cross-claim or counterclaim in a lawsuit) alleging that the Work
              or a Contribution incorporated within the Work constitutes direct
              or contributory patent infringement, then any patent licenses
              granted to You under this License for that Work shall terminate
              as of the date such litigation is filed.
        
           4. Redistribution. You may reproduce and distribute copies of the
              Work or Derivative Works thereof in any medium, with or without
              modifications, and in Source or Object form, provided that You
              meet the following conditions:
        
              (a) You must give any other recipients of the Work or
                  Derivative Works a copy of this License; and
        
              (b) You must cause any modified files to carry prominent notices
                  stating that You changed the files; and
        
              (c) You must retain, in the Source form of any Derivative Works
                  that You distribute, all copyright, patent, trademark, and
                  attribution notices from the Source form of the Work,
                  excluding those notices that do not pertain to any part of
                  the Derivative Works; and
        
              (d) If the Work includes a "NOTICE" text file as part of its
                  distribution, then any Derivative Works that You distribute must
                  include a readable copy of the attribution notices contained
                  within such NOTICE file, excluding those notices that do not
                  pertain to any part of the Derivative Works, in at least one
                  of the following places: within a NOTICE text file distributed
                  as part of the Derivative Works; within the Source form or
                  documentation, if provided along with the Derivative Works; or,
                  within a display generated by the Derivative Works, if and
                  wherever such third-party notices normally appear. The contents
                  of the NOTICE file are for informational purposes only and
                  do not modify the License. You may add Your own attribution
                  notices within Derivative Works that You distribute, alongside
                  or as an addendum to the NOTICE text from the Work, provided
                  that such additional attribution notices cannot be construed
                  as modifying the License.
        
              You may add Your own copyright statement to Your modifications and
              may provide additional or different license terms and conditions
              for use, reproduction, or distribution of Your modifications, or
              for any such Derivative Works as a whole, provided Your use,
              reproduction, and distribution of the Work otherwise complies with
              the conditions stated in this License.
        
           5. Submission of Contributions. Unless You explicitly state otherwise,
              any Contribution intentionally submitted for inclusion in the Work
              by You to the Licensor shall be under the terms and conditions of
              this License, without any additional terms or conditions.
              Notwithstanding the above, nothing herein shall supersede or modify
              the terms of any separate license agreement you may have executed
              with Licensor regarding such Contributions.
        
           6. Trademarks. This License does not grant permission to use the trade
              names, trademarks, service marks, or product names of the Licensor,
              except as required for reasonable and customary use in describing the
              origin of the Work and reproducing the content of the NOTICE file.
        
           7. Disclaimer of Warranty. Unless required by applicable law or
              agreed to in writing, Licensor provides the Work (and each
              Contributor provides its Contributions) on an "AS IS" BASIS,
              WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
              implied, including, without limitation, any warranties or conditions
              of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
              PARTICULAR PURPOSE. You are solely responsible for determining the
              appropriateness of using or redistributing the Work and assume any
              risks associated with Your exercise of permissions under this License.
        
           8. Limitation of Liability. In no event and under no legal theory,
              whether in tort (including negligence), contract, or otherwise,
              unless required by applicable law (such as deliberate and grossly
              negligent acts) or agreed to in writing, shall any Contributor be
              liable to You for damages, including any direct, indirect, special,
              incidental, or consequential damages of any character arising as a
              result of this License or out of the use or inability to use the
              Work (including but not limited to damages for loss of goodwill,
              work stoppage, computer failure or malfunction, or any and all
              other commercial damages or losses), even if such Contributor
              has been advised of the possibility of such damages.
        
           9. Accepting Warranty or Additional Liability. While redistributing
              the Work or Derivative Works thereof, You may choose to offer,
              and charge a fee for, acceptance of support, warranty, indemnity,
              or other liability obligations and/or rights consistent with this
              License. However, in accepting such obligations, You may act only
              on Your own behalf and on Your sole responsibility, not on behalf
              of any other Contributor, and only if You agree to indemnify,
              defend, and hold each Contributor harmless for any liability
              incurred by, or claims asserted against, such Contributor by reason
              of your accepting any such warranty or additional liability.
        
           END OF TERMS AND CONDITIONS
        
           APPENDIX: How to apply the Apache License to your work.
        
              To apply the Apache License to your work, attach the following
              boilerplate notice, with the fields enclosed by brackets "[]"
              replaced with your own identifying information. (Don't include
              the brackets!)  The text should be enclosed in the appropriate
              comment syntax for the file format. We also recommend that a
              file or class name and description of purpose be included on the
              same "printed page" as the copyright notice for easier
              identification within third-party archives.
        
           Copyright [yyyy] [name of copyright owner]
        
           Licensed under the Apache License, Version 2.0 (the "License");
           you may not use this file except in compliance with the License.
           You may obtain a copy of the License at
        
               http://www.apache.org/licenses/LICENSE-2.0
        
           Unless required by applicable law or agreed to in writing, software
           distributed under the License is distributed on an "AS IS" BASIS,
           WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
           See the License for the specific language governing permissions and
           limitations under the License.
        
Project-URL: Homepage, https://github.com/ChengJunyan1/lllm
Project-URL: Source, https://github.com/ChengJunyan1/lllm
Project-URL: Documentation, https://lllm.one
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: openai>=1.40.0
Requires-Dist: pydantic>=2.7.0
Requires-Dist: tiktoken>=0.7.0
Requires-Dist: numpy>=1.26.0
Requires-Dist: requests>=2.31.0
Requires-Dist: tqdm>=4.66.0
Requires-Dist: filelock>=3.13.0
Requires-Dist: nbformat>=5.10.0
Requires-Dist: jupyter-client>=8.6.0
Requires-Dist: litellm>=1.40.0
Requires-Dist: Pillow>=10.0.0
Requires-Dist: tomli>=2.0.1; python_version < "3.11"
Provides-Extra: dev
Requires-Dist: pytest>=8.0.0; extra == "dev"
Requires-Dist: pytest-asyncio>=0.23.0; extra == "dev"
Requires-Dist: python-dotenv>=1.0.0; extra == "dev"
Dynamic: license-file

<div align="center">
  <img src="https://raw.githubusercontent.com/ChengJunyan1/lllm/main/assets/LLLM-logo.png" alt="LLLM Logo" width="600"/>
  <br>
  <h1>Low-Level Language Model (LLLM) </h1>
  <h4>Lightweight framework for building complex agentic systems</h4>
</div>
<p align="center">
  <a href="https://lllm.one">
    <img alt="Docs" src="https://img.shields.io/badge/API-docs-red">
  </a>
  <a href="https://github.com/chengjunyan1/lllm/tree/main/examples">
    <img alt="Examples" src="https://img.shields.io/badge/API-examples-994B00">
  </a>
  <a href="https://pypi.org/project/lllm-core/">
    <img alt="Pypi" src="https://img.shields.io/pypi/v/lllm-core.svg">
  </a>
  <a href="https://github.com/chengjunyan1/lllm/blob/main/LICENSE">
    <img alt="GitHub License" src="https://img.shields.io/github/license/chengjunyan1/lllm">
  </a>
  <a href="https://discord.gg/aTah8r7YpM">
    <img alt="Discord" src="https://img.shields.io/badge/Discord%20-%20blue?style=flat&logo=discord&label=LLLM&color=%235B65E9">
  </a>
</p>

LLLM is a lightweight framework for developing **advanced agentic systems**. Allows users to build a complex agentic system with <100 LoC. Prioritizing minimalism, modularity, and reliability, it is specifically suitable for complex and frontier agentic systems beyond daily chat. While these fields require deep architectural customization and highly diverse demands, developers and researchers often face the burden of managing low-level complexities such as exception handling, output parsing, and API error management. LLLM bridges this gap by offering necessary abstractions that balance high-level encapsulation with the simplicity required for flexible experimentation. It also tries to make the code plain, compact, easy-to-understand, with less unnecessary indirection, thus easy for customization for different projects' needs, to allow researchers and developers to focus on the core research questions. See https://lllm.one for detailed documentation.


Key design ideas: agentic system as a program (agents + prompts + tactics), dialog as each agent's internal mental state, configuration as declaration. See the [Architecture Overview](https://lllm.one/architecture/overview/) for the full design philosophy.


## Installation

```bash
pip install lllm-core
```


## Quick Start

No configuration needed. Set your API key and run:

```bash
pip install lllm-core
export OPENAI_API_KEY=sk-...   # or ANTHROPIC_API_KEY, etc.
```

```python
from lllm import Tactic

# One-line chat
response = Tactic.quick("What is the capital of France?")
print(response.content)

# Get the agent and chat
response, agent = Tactic.quick("What is the capital of France?", return_agent=True)
print(response.content)
print(agent.name)

# Get the agent only
agent = Tactic.quick() # by default the system prompt is "You are a helpful assistant."
print(agent.name)

# Get the agent and chat with a custom system prompt
agent = Tactic.quick(system_prompt="You are a helpful assistant.", model="gpt-4o")
agent.open("chat")
agent.receive("What is the capital of France?")
print(agent.respond().content)

# Chat with a custom system prompt 
response = Tactic.quick("What is the capital of France?", system_prompt="You are a helpful assistant.")
print(response.content)

# Chat with a custom system prompt and get the agent
response, agent = Tactic.quick("What is the capital of France?", system_prompt="You are a helpful assistant.", return_agent=True)
print(response.content)
print(agent.name)
```

That's it — no `lllm.toml`, no folder structure, no subclassing.

**Supported providers** (via [LiteLLM](https://github.com/BerriAI/litellm)):
- OpenAI: `model="gpt-4o"` + `OPENAI_API_KEY`
- Anthropic: `model="claude-opus-4-6"` + `ANTHROPIC_API_KEY`
- Any other LiteLLM-supported provider

### Growing your project

As your project grows, you can gradually introduce structure:

1. **Add a config file** — copy `lllm.toml.example` to `lllm.toml` and point it at your prompt/proxy folders
2. **Move prompts to files** — put `.md` files under a `prompts/` folder; they auto-register via discovery
3. **Define agents in YAML** — use `AgentSpec` configs for multi-agent tactics
4. **Subclass `Tactic`** — implement `call()` to orchestrate multiple agents

See `examples/` for concrete patterns at each stage.

## Examples

See [`examples/README.md`](examples/README.md) for the full index. A quick map:

**Standalone scripts** — one API key, no extra setup:

| Script | What it shows |
|--------|--------------|
| [`basic_chat.py`](examples/basic_chat.py) | `Tactic.quick()` — zero-config single-agent chat |
| [`multi_turn_chat.py`](examples/multi_turn_chat.py) | Multi-turn history, dialog `fork()` |
| [`tool_use.py`](examples/tool_use.py) | `@tool` decorator, function calling, diagnostics |
| [`structured_output.py`](examples/structured_output.py) | `Prompt(format=MyModel)` — Pydantic structured output |

**Advanced scripts** (in [`examples/advanced/`](examples/advanced/)) — auto-detect provider from env:

| Script | What it shows |
|--------|--------------|
| [`multi_agent_tactic.py`](examples/advanced/multi_agent_tactic.py) | Custom `Tactic` subclass, two-agent pipeline |
| [`session_logging.py`](examples/advanced/session_logging.py) | SQLite `LogStore`, session querying |
| [`batch_processing.py`](examples/advanced/batch_processing.py) | `bcall()`, `ccall()` concurrent execution |

**Full package example** — [`examples/code_review_service/`](examples/code_review_service/):

A self-contained LLLM package with `lllm.toml`, prompt files, tactic files, and YAML configs with inheritance — wrapped as a FastAPI HTTP service. See [`code_review_service/README.md`](examples/code_review_service/README.md) for full documentation.

```bash
cd examples/code_review_service
export OPENAI_API_KEY=sk-...
python service.py --demo            # CLI demo, no web server
python service.py                   # FastAPI on :8080  (pip install fastapi uvicorn)
LLLM_CONFIG_PROFILE=pro python service.py --demo  # production config
```

### Proxies & Tools

Built-in proxies (financial data, search, etc.) register automatically when their modules are imported. If you plan to call `Proxy()` directly, either:

1. Set up an `lllm.toml` with a `[proxies]` section so discovery imports your proxy folders on startup, or
2. Call `load_builtin_proxies()` to import the packaged modules, or manually import the proxies you care about (e.g., `from lllm.proxies.builtin import exa_proxy`).

This mirrors how prompts are auto-registered via `[prompts]` in `lllm.toml`.

Once proxies are loaded you can check what is available by calling `Proxy().available()`.

### Auto-Discovery Config

A starter `lllm.toml.example` lives in the repo root. Copy it next to your project entry point and edit the folder paths:

```bash
cp lllm.toml.example lllm.toml
```

The sample configuration points to `examples/autodiscovery/prompts/` and `examples/autodiscovery/proxies/`, giving you a working prompt (`examples/hello_world`) and proxy (`examples/sample`) to experiment with immediately.

## Testing & Offline Mocks

TODO 

## Testing

Run tests with pytest:

```bash
pytest tests/
```

## Experimental Features

- **Computer Use Agent (CUA)** – `lllm.tools.cua` offers browser automation via Playwright and the OpenAI Computer Use API. It is still evolving and may change without notice.
- **Responses API Routing** – opt into OpenAI’s Responses API by setting `api_type = "response"` per agent. This enables native web search/computer-use tools but currently targets OpenAI only.
- **Skills (WIP)** – For defining more complex base agents.


# Roadmap

## v0.1.0 Refactoring 
- [x] Refactor providers system: LiteLLM invoker (invokers/)
- [x] Refactor registry to runtime (runtime.py), and discovery system (discovery.py)
- [x] Refactor prompt model and prompt management (prompt.py)
  - [x] Prompt composition and inheritance
  - [x] More graceful tool (link_function)
  - [x] Clearing up ad-hoc designs
  - [x] Better parsing system, more intuitive argument passing
  - [x] Better handling system for error, exception, interrupt
- [x] Refactor message and dialog model/state management, better arg passing (dialog.py)
- [x] Refactor agent model, agent call (agent.py)
- [x] Refactor tactics (tactic.py)
- [x] Refactor config and package system (config.py, lllm.toml, etc.)
  - [x] Package system with `lllm.toml` — namespaced resource URLs (`pkg.section:resource`)
  - [x] Dependency tree with recursive loading and cycle detection
  - [x] Alias support (`as` for packages, `under` for virtual folder prefixes)
  - [x] Unified ResourceNode-based registry with lazy loading
  - [x] Named runtimes (`load_runtime`, `get_runtime`) for parallel experiments
  - [x] Auto-initialization from project root `lllm.toml`
  - [x] Agent config YAML: `global` defaults, `agent_configs` list, `base` inheritance with deep merge
  - [x] `AgentSpec` with inline `system_prompt` or `system_prompt_path` resolution
  - [x] `resolve_config()` for recursive config inheritance
  - [x] Convenience loaders: `load_prompt`, `load_tactic`, `load_proxy`, `load_config`, `load_resource`
- [x] Logger (cli logging), replayable logging system, and printing system (log.py, utils.py)
  - [x] `LogStore` with pluggable backends (`LocalFileBackend`, `SQLiteBackend`, `NoOpBackend`)
  - [x] Tag-based indexing and filtering, cost aggregation, export helpers
  - [x] Stable `pkg::name` tactic identity independent of file layout and aliases
  - [x] `ColoredFormatter` and `setup_logging` for terminal output
  - [x] Convenience factories: `local_store`, `sqlite_store`, `noop_store`
- [x] Fast mode, 5-line code to build a simple system with no configuration.


## TODOs

- [ ] Proxy-based tool-calling, mini in-dialog interpreter (proxies/)
- [ ] Analysis tools based on the logging system, e.g., cost analysis, dialog analysis, etc. Basically, a GUI for the logging DB, and exporting an app with default dashboards using like Streamlit, Dash, Panel, etc.
- [ ] Support skills in agent config, see https://agentskills.io
- [ ] Default Context Manager for prune over-size dialogs
- [ ] Better sandbox, e.g., browser sandbox, code sandbox, etc. maybe use sandbox wheels (sandbox/)
- [ ] Tactics, Prompts, Proxies, Configs, etc. sharing system.


## Future Roadmap

- [ ] Gradient mode for tuning/training



<!-- 
git status          # ensure no stray files you don’t want in the sdist
rm -rf dist build *.egg-info    # clean

python -m build     # creates dist/lllm-<version>.tar.gz and .whl

# test locally
python -m venv /tmp/lllm-release
source /tmp/lllm-release/bin/activate
pip install dist/lllm-<version>-py3-none-any.whl
python -c "import lllm; print(lllm.__version__)"
deactivate

# upload
python -m twine upload dist/*

# push tag
git tag -a v0.0.1.3 -m "Release 0.0.1.3"
git push origin main --tags 

# update doc
mkdocs build --strict
mkdocs gh-deploy --force --clean

-->

